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International Journal of Engineering Applied Sciences and Technology, 2021 Vol. 5, Issue 11, ISSN No. 2455-2143, Pages 262-266 Published Online March 2021 in IJEAST (http://www.ijeast.com) DRS ASSISTING UMPIRE USING COMPUTER VISION Ms. Kajal Shirke, Ms. Varsha Warise, Ms. Pooja Waykule Student, Information Technology Engineering, Bharati Vidyapeeth College of Engineering, Navi Mumbai, Maharashtra, India Prof. S.N. Mhatre Assistant Professor, Dept. of Information Technology, Bharati Vidyapeeth College of Engineering, Navi Mumbai, Maharashtra, India Abstract - A fair decision is crucial in any of the game to give of the decisions. If this can be achieved with the help of technology, justice to the game. Any wrong decision due to human then the game will be more fair and enjoyable. Previously proposed misperception may fate the result of the game. Computer vision researches regarding this field have tried to solve the problem, but and Image processing techniques have been mentioned in the these are infeasible, costly and prone to error because of the usage of literature review which used multiple cameras for sensors on field and bowlers. On the other hand, we have proposed demonstration. This paper focuses on a system which helps in computer vision based approach in this paper which does not need making the decisions to assist the umpire in taking the extra infrastructure because it will get video feed from broadcasting decisions such as no-ball, LBW i.e. Leg before wicket, Run out, cameras. Our proposed method is expected to perform better and low stump out, etc with the help of smartphone camera of good cost in operating due to no infield sensor and other devices. quality. The Decision review system (DRS) aims to give decisions like The remaining portion of the paper is organized as Section II run-out and stump-out. Tkinter is used to develop the GUI of includes brief picture about the Related Work and Proposed system. DRS. Object classification and object recognition is Section III includes Working methodology and Implementation. implemented using Histogram of Gradients (HOG) and Section IV includes Results which discuss briefly about the the Support Vector Machine (SVM). To detect the cricket ball decisions got from using the various computer vision algorithms. from the video we optimized and used frame subtraction, Finally, Section V includes conclusion and future scope that lay contour detection and minimum enclosing circle algorithms down the outcomes of proposed work. using OpenCV library. Linear regression and quadratic regression are used to track and predict the motion of the ball Section II from video source. VPython is used for the visual representation. II. LITERATURE SURVEY Section I 2.1 Related work In the past few technologies was developed, one of the prominent I. INTRODUCTION ones being “Application of Computer Vision in Cricket: Foot 1.1 Background: Overstep No-ball Detection” proposed by AZM Ehtesham Chowdhury, Md Shamsur Rahim, Md Asif Ur Rahman [2] where [1] In every cricket match, umpires are responsible for deciding image subtraction is used and this system works on only the bowler’s the approval of a ball bowled by a bowler. There are many front foot and bowling end popping crease. scenarios when a delivery is disapproved by umpires. Decisions like LBW, no ball, run out and stump out requires some minutes “Cricket umpire assistance and ball tracking system using a single in certain cases using television replay. So umpires make their smartphone camera” by Udit Arora, Sohit Verma, Sarthak Sahni, and decisions on their perception, but human perception cannot be Tushar Sharma [3] proposed a system that involved computer vision accurate all the time. Besides, it is not always possible to algorithms to detect, identify and track the cricket ball and machine conclude the accurate judgment because of the limitations of learning techniques to optimize and further predict various results and existing technology and this creates mass confusion and debates decisions. among the viewers and cricket lovers. The on-field umpire at the bowler’s end signals a square mime of a TV screen to prompt the In another research paper, B.L.Velammal, P. Anandha Kumar third umpire to review the decision. The third umpire initially proposed “An Efficient Ball Detection Framework for Cricket” [4]. In checks if it’s a legal delivery before proceeding to watch the that non-ball objects and ball objects are identified. Region Growing replays to make an lbw or other decisions. segmentation is chosen for segmentation. After performing segmentation, the ball and non-ball objects are differentiate based on 1.2 Aim and Objective: shape properties. The non-ball objects are eliminated and resulting It is necessary to eradicate the debate to increase the acceptability frames consists of only ball object. The ball objects are used further to 262 International Journal of Engineering Applied Sciences and Technology, 2021 Vol. 5, Issue 11, ISSN No. 2455-2143, Pages 262-266 Published Online March 2021 in IJEAST (http://www.ijeast.com) detect the ball. “Implementation of Augmented Reality in Cricket for Ball Tracking and Automated Decision Making for No ball” by Nikhil Batra, Harsh Gupta, Nakul Yadav, Anshika Gupta, Amita Yadav [5] proposed a system that determines whether a ball is a no-ball or wide ball. The system applies different techniques like canny edge detector, Hough line transform algorithms, Douglas Peucker algorithm contour. No More Third Umpires” by Alex Joseph, Alistar Fernandez, Jasir Ahamed P.A., Treesa Joseph [6] proposed a system that uses image and video processing techniques, which automates the role of the third umpire. 2.2 Problem statement In India, everyone is enthusiastic about cricket. Many training academies, competitions, and even though gully cricket restricts Figure 3:Proposed System the use of decision review system for making a decision because of its high cost. Because of that many unfair decision was given 3.1 Ball Detection by the umpire which is not good for both the teams, as a result, many controversies have happened. Our project aims to develop a Frame differencing technique is used to extract frames which further computer system that helps the umpire for making a decision in converted into grayscale. These frames are then used extract HOG cricket at a low cost and can be used at various competitions, features which then fed to SVM model which is built using OpenCV academies and even in gully cricket. SVM library is then used to detect the ball by using frame subtraction method. Positive and negative data samples are collected III. PROPOSED SYSTEM which are also used to extract HOG features. 3.2 Ball Tracking Our project “DRS assisting umpire using computer vision” is implemented using Python and Tkinter. GUI of our project i.e. SVM model is used to detect the exact presence of the ball where DRS gives options to choose from to the user which contains the ball is detected in the particular frame. A separate file is created Stump out, Run out, No ball and LBW decisions. Stump out and to store the coordinates of the ball which are obtains as ‘x’ and ‘y’ Run out can be decided by playing the source video in slow or coordinates. fast motion. Further decisions like LBW and No Ball can be implemented by extracting frames through the source video. Ball 3.3 Batsman Detection and Tracking detection and Batsman height detection is done from the extracted OpenCV ‘s built-in People Detector SVM models are used to detect frames. The detected ball coordinates are further used for ball the batsman from the provided video. The batsman movement is tracking. 3D coordinates are mapped into 3D coordinates and tracked by limiting the search window to the neighborhood of the smoothen using regression techniques. Visualization is first detection which is displayed on the frame. implemented through Vpython which shows results for all these decisions. 3.4 Mapping 2D coordinates to 3D world coordinates The 2D coordinates of the tracked ball which are obtained after series of transformation using Minimum Enclosing Circle algorithm are then mapped into 3D world coordinates according to the cricket pitch dimensions. The z-coordinates i.e. depth is obtained by comparing it with the radius which is obtained at the beginning vs. Obtained at the end of the pitch. It is then scaled the ratio to the length of the pitch. 3.5 3D Visualization of Tracked ball and Cricket Pitch The obtained x,y and z coordinates are used to visualize the objects in 3D using VPython visualization library. For better visualization, linear and quadratic regression is applied over various dimensions. 263 International Journal of Engineering Applied Sciences and Technology, 2021 Vol. 5, Issue 11, ISSN No. 2455-2143, Pages 262-266 Published Online March 2021 in IJEAST (http://www.ijeast.com) batsmen fails to make his ground while running between the Section III wickets, the batsman is determined as a run-out. The batsmen must have something behind the line to be safe except they are on the IV. WORKING METHODOLOGY same side, in that case, the batsman further away from the stumps determines as run-out. A fielder must touch the ball before it hits the We developed a system that helps the third umpire to make a wicket for the run-out to be genuine. If the batsman hits the ball and decision on various calls on the field. it strikes the stumps on the other end while the other side batsman or non-striker is out of the crease and the bowler has touched the ball 4.1 DRS Gui before it hits the wicket then it will be determined as run-out. It Provides facilities to give any decision like No-ball, Stump- out, LBW and Run out.
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